import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import cv2 as cv
from matplotlib import pyplot as plt
import os
from extract_center import CenterExtracter
plt.rcdefaults()
c = CenterExtracter()
img = c._read_image_("../data/images1/34.jpg")
img = c._subtract_image_(img)
img = c._crop_(img, 0, 0, 300, 300)
c._show_image_(img)
images = os.listdir(r"C:\Users\harik\Desktop\mini-project\data\images1")
type(img)
images = [i for i in images if i.endswith(".jpg")]
def center_using_opencv(image):
src = cv.imread(image, cv.IMREAD_COLOR)
# Check if image is loaded fine
if src is None:
print ('Error opening image!')
print ('Usage: hough_circle.py [image_name -- default ' + image + '] \n')
gray = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
gray = cv.medianBlur(gray, 5)
rows = gray.shape[0]
circles = cv.HoughCircles(gray, cv.HOUGH_GRADIENT, 1, rows / 8,
param1=100, param2=30,
minRadius=1, maxRadius=30)
if circles is not None:
circles = np.uint16(np.around(circles))
for i in circles[0, :]:
center = (i[0], i[1])
# circle center
cv.circle(src, center, 1, (0, 100, 100), 3)
# circle outline
radius = i[2]
cv.circle(src, center, radius, (255, 0, 255), 3)
return center, radius
else:
return (None, None), None
center_using_opencv("../data/images1/10.jpg")
import random
plt.figure(figsize=(30, 30), )
all_imgs = list(range(len(images)))
for i in range(49):
j = random.choice(all_imgs)
directory = r"C:\Users\harik\Desktop\mini-project\data\Images"
directory = f"{directory}\{j}.jpg"
img = plt.imread(directory)
img = img[380:700, 820:1300]
c = centers[j]
plt.subplot(7, 7, i+1)
plt.imshow(img, cmap='gray')
plt.title(directory.split("\\")[-1])
plt.hlines(c[1]-380, 0, img.shape[1], color='r')
plt.vlines(c[0]-820, 0, img.shape[0], color='r')
plt.axis('off')
# plt.scatter(c[0], c[1], color='red')
plt.title("Centers Using OpenCV")
plt.annotate("With OpenCV", (0, 0), (0, -30), xycoords='axes fraction', textcoords='offset points', va='top', fontsize=30)
plt.tight_layout()
plt.savefig("sample_with_opencv.jpg")